get_data

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, openWorld, and non-destructive, so safety is covered. The description adds genuinely new behavior: results are capped at max_rows rows as a table, the response also carries the total count and a download URL covering the whole selection, and the returned citation must be surfaced to the user with any use of the data — a licensing obligation not present in any structured field. That is meaningful context beyond the annotations, though it does not discuss truncation semantics or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three compact sentences with the filter scope front-loaded, followed by the return contract and the citation requirement. No filler, no restatement of the tool name, and each sentence carries distinct information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 14-parameter query tool with full schema coverage and an output schema, the description covers scope, the row-cap-plus-download-URL pattern that resolves the truncation concern, and the citation duty. What is missing is minor: it does not note that certain filters (e.g. cruise, height) apply only to particular dataset types, though the schema covers this per-parameter.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so every one of the 14 parameters is already documented, including exclusive end dates, case-sensitive station ids, and the apply_qc default. The description only restates the filter categories (box, time, station, cruise, height, quality control) without adding syntax, interaction, or precedence detail beyond the schema. Baseline 3 applies when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

"Observations for one variable, filtered by box, time, station, cruise, height and quality control" gives a specific verb (retrieve observations), a specific resource (a single variable's data), and enumerates the filter axes. This clearly separates it from sibling tools like aggregate, estimate, and describe_variable, which operate on variables rather than returning raw observations. It stops short of naming those siblings explicitly, so it lands at 4 rather than 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit when-to-use / when-not-to-use statement and no pointer to alternatives such as aggregate for summarised results or search_variables for obtaining the required id. Usage is only implied by the phrase "Observations for one variable" and by the citation obligation at the end. An agent can infer the purpose but must reason about sibling selection on its own.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.